# ---- Datasets
dat1 <- readRDS('data/Panama2012.RDS') %>% mutate(PlaceName = 'Darien', id = stringr::str_sub(dataset_id, 1, 3))
dat2 <- readRDS('data/Panama2017.RDS') %>% mutate(PlaceName = 'Mogue', id = stringr::str_sub(dataset_id, 1, 3))
dat3 <- readRDS('data/Panama2012_places.RDS')%>% mutate(survey = dataset_id)
dat0 <- rbind(dat3, dat1, dat2) %>% filter(id %in% c('005'))
dat0$virus[dat0$virus=='UNA'] <- 'UNAV'
dat0 <- dat0 %>% mutate(counts = pos,
survey = paste(virus,tsur, PlaceName, id)) %>%
arrange(desc(survey)) %>% mutate(age_mean_f = floor((age_min + age_max)/2))
rm(dat1, dat2, dat3)
(datasets <- unique(dat0$survey))
## [1] "VEEV 2017 Mogue 005" "VEEV 2012 Tamar 005" "VEEV 2012 Real 005"
## [4] "VEEV 2012 Pi-Pi 005" "VEEV 2012 Merca 005" "VEEV 2012 Darien 005"
## [7] "VEEV 2012 Aruza 005" "UNAV 2017 Mogue 005" "MADV 2017 Mogue 005"
## [10] "MADV 2012 Tamar 005" "MADV 2012 Real 005" "MADV 2012 Pi-Pi 005"
## [13] "MADV 2012 Merca 005" "MADV 2012 Darien 005" "MADV 2012 Aruza 005"
for (s in datasets)
{
dat <- filter(dat0, survey == s) %>% arrange(age_mean_f) %>%
mutate(birth_year = tsur - age_mean_f)
res1 <- fFitModel(model1, dat)
res2 <- fFitModel(model2, dat)
plot_res1 <- fPlotModel(res1, dat, 'constant', 'uniform')
plot_res2 <- fPlotModelDecades(res2, dat, 'decades', 'student_t')
grid.arrange(plot_res1, plot_res2, nrow =1)
res_survey <- list(dat = dat,
mod1 = res1,
mod2 = res2)
saveRDS(res_survey, paste0('res_final_10000/', s, '.RDS' ))
rm(dat, res1, res2, plot_res1, plot_res2, res_survey)
}














